Resources, mortality, and disease ecology: Importance of positive feedbacks between host growth rate and pathogen dynamics

This is an Accepted Manuscript of an article published by Taylor & Francis in Israel Journal of Ecology and Evolution in 2015, available online: http://www.tandfonline.com/10.1080/15659801.2015.1035508.Resource theory and metabolic scaling theory suggest that the dynamics of a pathogen within a host should strongly depend upon the rate of host cell metabolism. Once an infection occurs, key ecological interactions occur on or within the host organism that determine whether the pathogen dies out, persists as a chronic infection, or grows to densities that lead to host death. We hypothesize that, in general, conditions favoring rapid host growth rates should amplify the replication and proliferation of both fungal and viral pathogens. If a host population experiences an increase in mortality, to persist it must have a higher growth rate, per host, often reflecting greater resource availability per capita. We hypothesize that this could indirectly foster the pathogen, which also benefits from increased within-host resource turnover. We first bring together in a short review a number of key prior studies which illustrate resource effects on viral and fungal pathogen dynamics. We then report new results from a semi-continuous cell culture experiment with SHIV, demonstrating that higher mortality rates indeed can promote viral proliferation. We develop a simple model that illustrates dynamical consequences of these resource effects, including interesting effects such as alternative stable states and oscillatory dynamics. Our paper contributes to a growing body of literature at the interface of ecology and infectious disease epidemiology, emphasizing that host abundances alone do not drive community dynamics: the physiological state and resource content of infected hosts also strongly influence host-pathogen interactions

Systemic Infection and Limited Replication of SHIV Vaccine Virus in Brains of Macaques Inoculated Intracerebrally with Infectious Viral DNA

AbstractSHIV deleted in two accessory genes, ΔvpuΔnef SHIVPPC, functioned well as a vaccine against later challenge with highly pathogenic SHIVKU, and it was able to reach the brain after oral inoculation of live virus. In this study, the proviral genome cloned into a plasmid was inoculated as DNA intracerebrally and spread systemically. Few regions of the brain had detectable proviral DNA by real-time PCR. Two measures of virus replication, detection of viral mRNA expression and circular proviral DNA, were negative for those brain regions, with the exception of the infection site in the right parietal lobe, whereas lymphoid tissues were positive by both measures. Histopathological analyses of all the sampled brain and spinal cord regions did not reveal any abnormalities. Despite intracerebral inoculation of the viral DNA, the brain was not targeted for high levels of virus replication

Resources, mortality, and disease ecology: importance of positive feedbacks between host growth rate and pathogen dynamics

<div><p>Resource theory and metabolic scaling theory suggest that the dynamics of a pathogen within a host should strongly depend upon the rate of host cell metabolism. Once an infection occurs, key ecological interactions occur on or within the host organism that determine whether the pathogen dies out, persists as a chronic infection, or grows to densities that lead to host death. We hypothesize that, in general, conditions favoring rapid host growth rates should amplify the replication and proliferation of both fungal and viral pathogens. If a host population experiences an increase in mortality, to persist it must have a higher growth rate, per host, often reflecting greater resource availability per capita. We hypothesize that this could indirectly foster the pathogen, which also benefits from increased within-host resource turnover. We first bring together in a short review a number of key prior studies which illustrate resource effects on viral and fungal pathogen dynamics. We then report new results from a semi-continuous cell culture experiment with SHIV, demonstrating that higher mortality rates indeed can promote viral proliferation. We develop a simple model that illustrates dynamical consequences of these resource effects, including interesting effects such as alternative stable states and oscillatory dynamics. Our paper contributes to a growing body of literature at the interface of ecology and infectious disease epidemiology, emphasizing that host abundances alone do not drive community dynamics: the physiological state and resource content of infected hosts also strongly influence host–pathogen interactions.</p></div

Quantification of Tetracycline Resistance Genes in Feedlot Lagoons by Real-Time PCR

A new real-time PCR method is presented that detects and quantifies three tetracycline resistance (Tc(r)) genes [tet(O), tet(W), and tet(Q)] in mixed microbial communities resident in feedlot lagoon wastewater. Tc(r) gene real-time TaqMan primer-probe sets were developed and optimized to quantify the Tc(r) genes present in seven different cattle feedlot lagoons, to validate the method, and to assess whether resistance gene concentrations correlate with free-tetracycline levels in lagoon waters. The method proved to be sensitive across a wide range of gene concentrations and provided consistent and reproducible results from complex lagoon water samples. The log(10) of the sum of the three resistance gene concentrations was correlated with free-tetracycline levels (r(2) = 0.50, P < 0.001; n = 18), with the geometric means of individual resistance concentrations ranging from 4- to 8.3-fold greater in lagoon samples with above-median tetracycline levels (>1.95 μg/liter by enzyme-linked immunosorbent assay techniques) than in below-median lagoon samples. Of the three Tc(r) genes tested, tet(W) and tet(Q) were more commonly found in lagoon water samples. Successful development of this real-time PCR assay will permit other studies quantifying Tc(r) gene numbers in environmental and other samples